Epitope fluctuation and immunogenicity

ABSTRACT

Systems and methods for computer-aided vaccine design may comprise performing one or more molecular dynamics simulations of a protein assembly having at least one epitope, determining a fluctuation measurement for the at least one epitope using the one or more molecular dynamics simulations, and predicting the immunogenicity of the protein assembly in response to the fluctuation measurement are disclosed.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application No.61/449,634, filed Mar. 5, 2011, the entire disclosure of which is herebyincorporated by reference.

TECHNICAL FIELD

The present disclosure relates generally to the role of epitopefluctuation in immunogenicity. More particularly, the present disclosurerelates to the use of epitope fluctuation measurements as part ofcomputer-aided vaccine design methods.

BACKGROUND ART

Vaccines for the prevention of cervical cancer by Human Papillomavirus(HPV) infection have been developed from the capsid of HPV viruses. Thevaccine Gardasil®, commercially available from Merck & Co. of WhitehouseStation, N.J., which is effective against four HPV types (HPV6, HPV11,HPV16, HPV18) and has been very successful in preventing HPV infection,is composed of virus-like particles (VLP). Upon vaccination,type-specific antibodies generated by the immune system are capable ofneutralizing HPV pathogens. As more than forty HPV infectious types havebeen identified, a need exists to expand the capabilities of currentvaccines to target a broader family of HPV viruses. Vaccineeffectiveness is tied to the immunogenicity of VLPs and the productionof neutralizing antibodies.

DISCLOSURE OF INVENTION

The present invention may comprise one or more of the features recitedin the appended claims and/or one or more of the following features andany combinations thereof.

According to one aspect, a computer-aided vaccine design method maycomprise performing one or more molecular dynamics simulations of aprotein assembly having at least one epitope, determining a fluctuationmeasurement for the at least one epitope using the one or more moleculardynamics simulations, and predicting the immunogenicity of the proteinassembly in response to the fluctuation measurement. In someembodiments, the protein assembly may be a virus-like particle. In otherembodiments, the protein assembly may be a pentamer.

In some embodiments, determining the fluctuation measurement for the atleast one epitope may comprise determining a distribution of backbonedihedral angles in conformational space. In other embodiments,determining the fluctuation measurement for the at least one epitope maycomprise calculating a root-mean-square deviation of epitopefluctuation. In such embodiments, calculating the root-mean-squaredeviation of epitope fluctuation may comprise summing fluctuations foreach backbone atom during the one or more molecular dynamics simulationsand dividing by a total number of backbone atoms.

In other embodiments, determining the fluctuation measurement for the atleast one epitope may comprise calculating a correlation matrix betweenthe at least one epitope and other structures in the protein assembly.In still other embodiments, determining the fluctuation measurement forthe at least one epitope may comprise analyzing a Fourier spectrum ofepitope fluctuation.

In some embodiments, predicting the immunogenicity of the proteinassembly in response to the fluctuation measurement may further comprisepredicting the immunogenicity of the protein assembly in response to atleast one other molecular descriptor of the protein assembly. The one ormore molecular dynamics simulations may be performed using a deductivemultiscale simulator. The computer-aided vaccine design method mayfurther comprise synthesizing a vaccine comprising the protein assembly.

According to another aspect, one or more computer readable media maycomprise a plurality of instructions which, when executed by one or moreprocessors, cause the one or more processors to perform one or moremolecular dynamics simulations of a protein assembly having at least oneepitope, determine a fluctuation measurement for the at least oneepitope using the one or more molecular dynamics simulations, andpredict the immunogenicity of the protein assembly in response to thefluctuation measurement. In some embodiments, the protein assembly maybe a virus-like particle. In other embodiments, the protein assembly maybe a pentamer.

In some embodiments, the plurality of instructions may cause the one ormore processors to determine the fluctuation measurement for the atleast one epitope, at least in part, by determining a distribution ofbackbone dihedral angles in conformational space. In other embodiments,the plurality of instructions may cause the one or more processors todetermine the fluctuation measurement for the at least one epitope, atleast in part, by calculating a root-mean-square deviation of epitopefluctuation. In such embodiments, the plurality of instructions maycause the one or more processors to calculate the root-mean-squaredeviation of epitope fluctuation by summing fluctuations for eachbackbone atom during the one or more molecular dynamics simulations anddividing by a total number of backbone atoms.

In other embodiments, the plurality of instructions may cause the one ormore processors to determine the fluctuation measurement for the atleast one epitope, at least in part, by calculating a correlation matrixbetween the at least one epitope and other structures in the proteinassembly. In still other embodiments, the plurality of instructions maycause the one or more processors to determine the fluctuationmeasurement for the at least one epitope, at least in part, by analyzinga Fourier spectrum of epitope fluctuation.

In some embodiments, the plurality of instructions may further cause theone or more processors to predict the immunogenicity of the proteinassembly in response to at least one other molecular descriptor of theprotein assembly. The plurality of instructions may cause the one ormore processors to perform the one or more molecular dynamicssimulations using a deductive multiscale simulator.

BRIEF DESCRIPTION OF DRAWINGS

The detailed description particularly refers to the accompanying figuresin which:

FIG. 1 is a diagram illustrating an all-atom description of the epitoperegions of a thermally equilibrated L1 HPV-protein;

FIG. 2A is a graph illustrating a dihedral distribution for an FG loopin an L1 protein, using a 10 ns trajectory;

FIG. 2B is a graph illustrating a dihedral distribution for an FG loopin an L1 protein of a pentamer simulation, using an 8 ns trajectory;

FIG. 2C is a graph illustrating a dihedral distribution for an FG loopin an L1 protein of a VLP simulation, using a 5 ns trajectory;

FIG. 3A is a graph illustrating a dihedral distribution for an HI loopin an L1 protein, using a 10 ns trajectory;

FIG. 3B is a graph illustrating a dihedral distribution for an HI loopin an L1 protein of a pentamer simulation, using an 8 ns trajectory;

FIG. 3C is a graph illustrating a dihedral distribution for an HI loopin an L1 protein of a VLP simulation, using a 5 ns trajectory;

FIG. 4A is a graph illustrating loop fluctuations for an FG loop of aprotein;

FIG. 4B is a graph illustrating loop fluctuations for an FG loop of apentamer;

FIG. 4C is a graph illustrating loop fluctuations for an FG loop of aVLP;

FIG. 5A is a graph illustrating loop fluctuations for an HI loop of aprotein;

FIG. 5B is a graph illustrating loop fluctuations for an HI loop of apentamer; and

FIG. 5C is a graph illustrating loop fluctuations for an HI loop of aVLP.

BEST MODE(S) FOR CARRYING OUT THE INVENTION

While the concepts of the present disclosure are susceptible to variousmodifications and alternative forms, specific exemplary embodimentsthereof have been shown by way of example in the drawings and willherein be described in detail. It should be understood, however, thatthere is no intent to limit the concepts of the present disclosure tothe particular forms disclosed, but on the contrary, the intention is tocover all modifications, equivalents, and alternatives consistent withthe present disclosure and appended claims.

In the following description, numerous specific details may be set forthin order to provide a more thorough understanding of the presentdisclosure. It will be appreciated, however, by one skilled in the artthat embodiments of the invention may be practiced without such specificdetails. Full software instruction sequences have not been shown indetail in order not to obscure the invention. Those of ordinary skill inthe art, with the included descriptions, will be able to implementappropriate functionality without undue experimentation.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etcetera, indicate that the embodimentdescribed may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Moreover, such phrasesare not necessarily referring to the same embodiment. Further, when aparticular feature, structure, or characteristic is described inconnection with an embodiment, it is submitted that it is within theknowledge of one skilled in the art to effect such feature, structure,or characteristic in connection with other embodiments whether or notexplicitly described.

Some embodiments of the invention may be implemented in hardware,firmware, software, or any combination thereof Embodiments of theinvention may be implemented as instructions carried by or stored on oneor more machine-readable media, which may be read and executed by one ormore processors. A machine-readable medium may be embodied as anydevice, mechanism, or physical structure for storing or transmittinginformation in a form readable by a machine (e.g., a computing device).For example, a machine-readable medium may be embodied as read onlymemory (ROM); random access memory (RAM); magnetic disk storage media;optical storage media; flash memory devices; mini- or micro-SD cards,memory sticks, electrical signals, and others.

The present disclosure observes that variations in immunogenicity canexist between viral capsid protein assemblies of various sizes (e.g.,between the L1 protein of HPV monomers, pentamers, and whole VLPs).These variations may be attributed to the intensity of fluctuations inepitope conformation for the various protein assemblies. The presentdisclosure validates this relationship between epitope fluctuation andimmunogenicity for the illustrative embodiment of HPV L1 proteinassemblies using molecular dynamics (MD) simulations. In theillustrative embodiment, epitope fluctuations were quantified viaroot-mean-square (RMS) deviation and features in the Fourier transformof dynamic changes in epitope structure. As epitope fluctuation affectsimmunogenicity (i.e., immune system recognition of an epitope may bemore reliable when the epitope is presented via a more stable deliverystructure), epitope fluctuation measurements can serve as one predictorof immunogenicity. As such, epitope fluctuation measurements may serveas part of computer-aided vaccine design methods.

As can be seen in FIG. 1, HPV VLPs look very much like the virus and areassembled out of 72 capsomers arranged on a T=7 icosahedral structure.The VLP surface has outwardly projecting loop regions that arerecognized by the immune system triggering the production of antibodiesspecific to VLP type. Neutralizing antibodies bind to surface regions ofthe viruses spanning these different loops. Different HPV types producedifferent antibodies with varying immunogenic response and reactivity.Type specificity arises from the diversity of loop conformations indifferent HPV types even though the sequence homology between differentHPV proteins is large. Neutralization assays of HPV 16 VLPs with humansera have previously identified the following five epitope regions: BC(residues 49 to 70), DE (residues 110 to 154), EF (residues 170 to 189),FG (residues 262 to 291), and HI (residues 347 to 360).

These epitope regions, which are labeled in FIG. 1, are more flexiblethan the rest of the protein and contain sites for antibody binding. TheFG and HI loops contain residues that bind to the monoclonal antibodyH.16.V5, as previously observed in experiments in which loopstransplanted from HPV16 VLPs to HPV11 proteins bind to H16.V5. H16.V5binds strongly to VLPs containing FG and HI loops and weakly to VLPshaving only the FG loop. Mutagenesis experiments, with deletion ofcertain H16.V5 epitopes mainly from residues in the HI loop and some inthe FG loop, show that epitope-deleted VLPs are unaffected in theirreactivity to human HPV sera—although their ability to bind H16.V5 isstrongly reduced. However, epitope deletion reduces immunogenicity ofthese VLPs by a factor of at least 10 to 20 as compared to wild-typeVLPs. Neutralization assays of human sera with HPV16 VLP epitopes showthat the three loops DE, EF, FG are each essential for binding and thatmultiple regions on these loops contribute to antibody binding.

HPV pentamers are also viable vaccine candidates, as they form the unitsof the larger VLPs and automatically display the epitope regions of thewhole VLP. HPV pentamers are significantly easier and morecost-efficient to produce than complete VLPs and, as stable particleswith smaller size, are also easier to analyze and simulate. However, thepentameric unit is expected to behave differently from the whole VLP,which is expected to be more stable. The role of VLP assembly in epitopedetermination and stability also needs to be clarified before pentamerscan be used as successful vaccines.

A structural study of HPV pentamers from different HPV types has showndifferences in conformation and reactivity among them. However, X-raydata cannot adequately resolve loop regions and does not provide muchinformation regarding the fluctuations of the loop regions. Based onX-ray crystallographic data, it has previously been concluded thatoverall pentamer conformation was almost the same within and outside theVLP, including the loop regions. However, the immunoglobulin density ofHPV pentamer induces antibodies 20 to 40 times lower than those producedby the complete VLP. Binding assays of pentamer and VLP with differentmonoclonal antibodies show that VLPs are generally more reactive (asmeasured in absorption units). In the case of the monoclonal antibodyH16.V5, the reactivity of the pentamer was only slightly lower than thatof the VLP, but was much smaller in other cases. Both of theseexperimental observations suggest that there are important structuraldifferences between VLPs and pentamers that have not been adequatelyresolved with X-ray data. The epitopes FG and HI are crucial for bindingto H16.V5, with HI playing a major role. Therefore, the presentdisclosure examines the differences in the binding and immunogenicity ofHPV pentamers, as compared to complete VLPs, using MD simulations ofthese systems.

The structural similarity of the epitope loop regions for the pentamerversus the VLP is believed to indicate that immunogenicity differencesare related to the temporal variability in epitope loop conformation(i.e., fluctuation). As such, epitope fluctuation differences arerelated to differences of the forces exerted by the remainder of thestructure. For example, a smaller assembly could be more highlyfluctuating than a larger one due to differences in total assembly massor flexibility of the assembly. The present disclosure reveals thesedifferences in immunogenicity via MD simulations by measuring quantitiesthat can distinguish atomic-level details in these systems. In otherwords, measurements of epitope fluctuation may serve as inputs to aquantitative structure-activity relationship (QSAR) vaccine designmethod, or to other vaccine design methods. Using epitope fluctuationmeasurements as inputs to a computer-aided vaccine design method maylead to more effective, thermally stable, and cost-effective vaccinedelivery systems.

It is contemplated that the MD simulations used to determine epitopefluctuation measurements may be performed using any suitable simulationsoftware. For instance, in some embodiments, MD simulations of proteinassemblies may be performed using a deductive multiscale simulator, suchas that described in PCT International Application No.PCT/US2012/020569, filed Jan. 7, 2012 (the entire disclosure of which ishereby incorporated by reference) and in Joshi et al., “MultiscaleSimulation of Microbe Structure and Dynamics,” 107 Progress inBiophysics & Molecular Biology 200-217 (2011) (the entire disclosure ofwhich is hereby incorporated by reference). In the illustrativeembodiment described below, the HPV16 (T=1) VLP, pentamer, and L1protein were simulated separately under the same conditions to identifydifferences in structure and fluctuations in these systems. Theseillustrative simulations were run using the NAMD software program, witha TIP3 model for water and a particle mesh Ewald for calculatinglong-range electrostatic forces. Five nanoseconds of simulations wereperformed for the VLP, eight nanoseconds of simulations were performedfor the HPV pentamer, and ten nanoseconds of simulations were performedfor the L1 protein.

According to the illustrative embodiment, the following measurements ofepitope fluctuation may be used, alone or in combination, to distinguishthese systems: (1) distribution of backbone loop dihedral and side-chaindihedral angles in conformational space, (2) fluctuations of the loopatoms from their average value, (3) correlation analysis of the loopswith each other and with regions that produce strong attractive orrepulsive forces, and (4) power spectrum of the Fourier modes of theloop motions. The loop dihedral angles, their region of variation, andthe fluctuations of the loop variables indicate the conformational spaceavailable to the epitopes. The magnitude of the fluctuations is ameasure of the entropy of the loops and determines their flexibility.The correlation matrix provides a measure of the interactions betweenthe different loops and provides additional information on importantlong-range forces exerted on loops that do not belong to the sameprotein. The Fourier spectral density gives the amplitude of wave-likemotions of the loops.

FIGS. 2A, 2B, and 2C illustrate the regions of variation of the backbonedihedral angles for loop FG in the L1 protein, pentamer, and VLP,respectively. FIGS. 3A, 3B, and 3C illustrate the regions of variationof the backbone dihedral angles for loop HI in the L1 protein, pentamer,and VLP, respectively. One thousand data points were retained in eachcase from the simulations, making these plots a measure of probabilitydistributions of loop conformations. As shown in FIGS. 2A-3C, loop HImaintains its native L1 conformation in pentamer and VLP, but loop FGoccupies a smaller region in VLP compared to pentamer, and much smallercompared to its conformation in L1 protein. Loop FG's large flexibilityin the protein appears diminished in pentamer and VLP. A structuralanalysis of the pentamer shows that loop HI from one pentamer isblanketed by loops EF and FG from its counterclockwise neighbor.Similarly, loop FG is blanketed by loops DE and HI from its clockwiseneighbor. This arrangement leads to stronger interactions between loopsFG and HI in pentamer and VLP than in L1 protein, where they are widelyseparated in space. The differences obtained in VLP and pentamer arealso notable in loop FG. Loop BC is distant from other loops andprojects out of the pentamer and VLP. As such, loop BC shows nosignificant differences in conformation between the three cases and mostlikely occupies a very wide conformational state. This result isexpected, as this loop projects outward from the pentamer and is moremobile than the other loops that interact with adjacent loops. Unlikeloop BC, loops DE and EF show minor differences in conformation. Loop DEis the longest of the loops and is expected to be more flexible thanother loops. The beta sheet core that forms the L1 protein remains verystable in the pentamer and VLP, but appears to bend in the isolatedprotein in the region near loop HI. In summary, this conformationalanalysis of the loops yielded few major differences except for loop FG.

The overall fluctuation of a loop from its average position is aquantity not directly measurable in structure determination techniqueslike X-ray crystallography and cry-EM. While structural determinationtechniques provide the most likely or average location of a loop region,measurements of the fluctuation of a loop region indicate otherimportant regions away from the average value. The loop fluctuation maybe computed by summing the fluctuations of each individual backbone atomin the loop and then dividing by the total number of atoms.

This measure is slightly different from usual RMS fluctuation, as itprovides a measure of the entropy of the loop conformation (as opposedto RMS fluctuation that measures fluctuation from a fixed structure).The loop fluctuation is also sensitive to overall displacement of aloop, unlike RMS fluctuation that is normally calculated by aligning twostructures (thereby eliminating any translational and rotationalmotions). The total fluctuations of each loop for VLP, L1 pentamer, andL1 protein are set forth below in Tables 1, 2, and 3, respectively, andmore detailed plots of the fluctuations of individual loop backboneatoms are illustrated in FIGS. 4A-4C (for loop FG) and in FIGS. 5A-5C(for loop HI). The loop fluctuations for loops FG and HI are the largestin the protein, significantly smaller in the pentamer, and even smallerin the VLP. The fluctuations of loops BC, DE, and EF are notdistinguishable between VLP and pentamer, but are much smaller than inthe protein. The very large fluctuations seen in the L1 protein (evenfor loop HI, which does not sample newer conformations, as shownearlier) are due to overall displacement of loop atoms from the attachedbeta sheet.

TABLE 1 Loop fluctuations for VLP Loop 2.5 ns 5 ns BC 2.9 4.4 DE 1.6 2.4EF 3.5 5.3 FG 1.4 1.5 HI 2.8 3.0

TABLE 2 Loop fluctuations for L1 pentamer Loop 4 ns 8 ns BC 2.1 3.5 DE1.4 2.5 EF 3.2 5.4 FG 1.9 3.1 HI 2.7 4.3

TABLE 3 Loop fluctuations for L1 protein Loop 5 ns 10 ns BC 5.4 16.2 DE6.9 11.6 EF 12.4 17.3 FG 12.0 20.2 HI 21.9 51.6

The differences in loop fluctuations between the three systems are aresult of complicated interactions between epitopes and proteins. Mostof these interactions appear to be entropy determined and to not involvedirect electrostatic forces. The loop interactions do not involvehydrogen bonds, as very few hydrogen bonds are formed with loop atoms.However, hydrogen bonds are formed between adjacent L1 in the pentamerin the core beta sheet region, making epitopes sensitive to backboneprotein fluctuations. The complete VLP is further stabilized by thehelix h4 posterior to the loop HI by interacting with helices h2 and h3from pentamers related to it at points of three-fold symmetry. Thisinteraction makes the pentamer in the VLP system less flexible and is afactor affecting stability of the epitopes. This interaction is alsoseen by comparing the spread between RMS deviations of pentamers andtheir individual proteins from their initial structure, with the spreadbeing larger in pentamer than in VLP.

The extent of the correlation between loops and other regions can becompared in the pentamer and VLP systems by calculating the correlationmatrix between important residues of the loop. This correlation analysisshows greater correlations between loops in VLP than in pentamer orprotein.

The extent of motion of individual loop regions may be measured by RMSdeviations from the initial structure for the VLP, pentamer, and L1protein at the end of a simulation trajectory (e.g., 1 ns). The resultsof an illustrative simulation are presented below in Table 4. The lastcolumn of Table 4 compares structures obtained in the different loopregions for VLP and pentamer. The loop HI samples a well-definedconformation in the VLP and the pentamer, but moves away from itsinitial state in the L1 protein, suggesting strong interactions betweenthis loop and neighboring monomers. The structures obtained at the endof the pentamer and VLP simulations have small deviation in the HIregion. Loop FG, on the other hand, becomes more unstable from pentamerto L1 protein. The deviation of the structures obtained in VLP andpentamer simulations are also quite large for this loop. Tracking thedeviation of the loops along a single trajectory indicates that theyincrease more in the pentamer than the VLP, except for loop HI thatappears to change little in the two cases. The results of the simulationdo not change significantly when the simulation is extended by anotherone nanosecond. The pentamer opens up after a long simulation, asmeasured by comparing the RMS deviation of an individual pentamer withthe average RMS deviation of the five L1 proteins forming it.

TABLE 4 RMS Deviation after 1 ns Simulation Region VLP Pentamer L1VLP/Pentamer BC .69 1.2 1.74 1.3 DE 1.63 1.37 1.56 2.2 EF .51 2.1 2.142.1 FG 1.1 1.55 2.56 2.3 HI .36 .66 1.02 0.5

Summarizing the molecular dynamics, the L1 protein loop conformationsare not very different from those in the bound pentamer and VLP,indicating that protein-protein interactions forming a pentamer and VLPdo not induce any new conformations, but rather stabilize existing onesby restricting the motions of loops FG and HI. The loop fluctuationmeasurement, which is a measure of the entropy of the loop, shows acorrelation between low entropy and higher immunogenicity. The loop HIis well defined and conserved in structure in the pentamer and VLP,whereas the loop FG is less conserved in the pentamer. This suggestsinter-pentameric interactions stabilizing the conformation of loop FGand reducing the entropy of loop HI.

According to the present disclosure, MD simulations of HPV VLPs,pentamers, and L1 proteins show a correlation between the highimmunogenicity observed for VLPs and the low entropy of loops FG and HI.This appears to be a result of differences in loop-loop and loop-proteininteractions for the VLP versus the pentamer. Methods to minimize theentropy of loops FG and HI may lead to higher immunogenicity of VLP andpentamer based vaccines. This epitope fluctuation-immunogenicityrelationship (validated herein for illustrative HPV L1 assemblies) maybe applied to other viral systems, using epitope fluctuations as aninput to a computer-aided vaccine design method. It will also beappreciated by those of skill in the art that even more reliableimmunogenicity prediction may be achieved by combining an epitopefluctuation measure with other molecular descriptors.

While the disclosure has been illustrated and described in detail in thedrawings and foregoing description, such an illustration and descriptionis to be considered as exemplary and not restrictive in character, itbeing understood that only illustrative embodiments have been shown anddescribed and that all changes and modifications that come within thespirit of the disclosure and the appended claims are desired to beprotected.

1. A computer-aided vaccine design method comprising: performing one ormore molecular dynamics simulations of a protein assembly having atleast one epitope; determining a fluctuation measurement for the atleast one epitope using the one or more molecular dynamics simulations;and predicting the immunogenicity of the protein assembly in response tothe fluctuation measurement.
 2. The computer-aided vaccine design methodof claim 1, wherein the protein assembly is a virus-like particle. 3.The computer-aided vaccine design method of claim 1, wherein the proteinassembly is a pentamer.
 4. The computer-aided vaccine design method ofclaim 1, wherein the one or more molecular dynamics simulations areperformed using a deductive multiscale simulator.
 5. The computer-aidedvaccine design method of claim 1, wherein determining the fluctuationmeasurement for the at least one epitope comprises determining adistribution of backbone dihedral angles in conformational space.
 6. Thecomputer-aided vaccine design method of claim 1, wherein determining thefluctuation measurement for the at least one epitope comprisescalculating a root-mean-square deviation of epitope fluctuation.
 7. Thecomputer-aided vaccine design method of claim 6, wherein calculating theroot-mean-square deviation of epitope fluctuation comprises summingfluctuations for each backbone atom during the one or more moleculardynamics simulations and dividing by a total number of backbone atoms.8. The computer-aided vaccine design method of claim 1, whereindetermining the fluctuation measurement for the at least one epitopecomprises calculating a correlation matrix between the at least oneepitope and other structures in the protein assembly.
 9. Thecomputer-aided vaccine design method of claim 1, wherein determining thefluctuation measurement for the at least one epitope comprises analyzinga Fourier spectrum of epitope fluctuation.
 10. The computer-aidedvaccine design method of claim 1, wherein predicting the immunogenicityof the protein assembly in response to the fluctuation measurementfurther comprises predicting the immunogenicity of the protein assemblyin response to at least one other molecular descriptor of the proteinassembly.
 11. The computer-aided vaccine design method of claim 1,further comprising synthesizing a vaccine comprising the proteinassembly.
 12. One or more non-transitory, computer readable mediacomprising a plurality of instructions which, when executed by one ormore processors, cause the one or more processors to: perform one ormore molecular dynamics simulations of a protein assembly having atleast one epitope; determine a fluctuation measurement for the at leastone epitope using the one or more molecular dynamics simulations; andpredict the immunogenicity of the protein assembly in response to thefluctuation measurement.
 13. The one or more non-transitory, computerreadable media of claim 12, wherein the protein assembly is a virus-likeparticle.
 14. The one or more non-transitory, computer readable media ofclaim 12, wherein the protein assembly is a pentamer.
 15. The one ormore non-transitory, computer readable media of claim 12, wherein theplurality of instructions cause the one or more processors to performthe one or more molecular dynamics simulations using a deductivemultiscale simulator.
 16. The one or more non-transitory, computerreadable media of claim 12, wherein the plurality of instructions causethe one or more processors to determine the fluctuation measurement forthe at least one epitope, at least in part, by determining adistribution of backbone dihedral angles in conformational space. 17.The one or more non-transitory, computer readable media of claim 12,wherein the plurality of instructions cause the one or more processorsto determine the fluctuation measurement for the at least one epitope,at least in part, by calculating a root-mean-square deviation of epitopefluctuation.
 18. The one or more non-transitory, computer readable mediaof claim 17, wherein the plurality of instructions cause the one or moreprocessors to calculate the root-mean-square deviation of epitopefluctuation by summing fluctuations for each backbone atom during theone or more molecular dynamics simulations and dividing by a totalnumber of backbone atoms.
 19. The one or more non-transitory, computerreadable media of claim 12, wherein the plurality of instructions causethe one or more processors to determine the fluctuation measurement forthe at least one epitope, at least in part, by calculating a correlationmatrix between the at least one epitope and other structures in theprotein assembly.
 20. The one or more non-transitory, computer readablemedia of claim 12, wherein the plurality of instructions cause the oneor more processors to determine the fluctuation measurement for the atleast one epitope, at least in part, by analyzing a Fourier spectrum ofepitope fluctuation.
 21. The one or more non-transitory, computerreadable media according to claim 12, wherein the plurality ofinstructions further cause the one or more processors to predict theimmunogenicity of the protein assembly in response to at least one othermolecular descriptor of the protein assembly.